Over the past few decades, several base isolation systems have been developed to enhance the performance of structures under extreme earthquake shaking intensities. Recently, to…
Abstract
Purpose
Over the past few decades, several base isolation systems have been developed to enhance the performance of structures under extreme earthquake shaking intensities. Recently, to achieve high energy dissipation capabilities, a new generation of multi-stage friction pendulum (FP) bearings known as the “Quintuple Friction Pendulum (QFP)” was introduced in the literature. With the help of its five effective pendula and nine operational regimes, this bearing's major benefits stem from its ability to accomplish complicated multi-stage adaptive behavior with smoothed loading and unloading when subjected to lateral forces.
Design/methodology/approach
Within the assessment context, five finite element models of reinforced concrete frames supported on QFP isolators with different properties will be developed in OpenSees. Thereafter, a set of 60 earthquakes will be analyzed using the nonlinear time history analysis approach, and the impact of each ground motion record's properties will be evaluated.
Findings
Overall, the study's findings have demonstrated that the characteristics of the isolator, combined with the type of earthquake being applied, have a substantial impact on the isolator's behavior.
Originality/value
Currently, no studies have examined the energy distribution of structural systems equipped with this type of isolation system while considering the influence of earthquake characteristics. Thus, this study is intended to extend the findings available in the literature by discussing and illustrating the distribution of strong ground motions input energy into highly nonlinear base-isolated systems that account for the bearing and superstructural materials' nonlinearity, geometric nonlinearity and leakage-prevented viscous damping nonlinearity. Besides, it investigates the influence of various earthquake characteristics on the energy dissipation of such buildings.
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Currently, many experimental studies on the properties and behavior of rubberized concrete are available in the literature. These findings have motivated scholars to propose…
Abstract
Purpose
Currently, many experimental studies on the properties and behavior of rubberized concrete are available in the literature. These findings have motivated scholars to propose models for estimating some properties of rubberized concrete using traditional and advanced techniques. However, with the advancement of computational techniques and new estimation models, selecting a model that best estimates concrete's property is becoming challenging.
Design/methodology/approach
In this study, over 1,000 different experimental findings were obtained from the literature and used to investigate the capabilities of ten different machine learning algorithms in modeling the hardened density, compressive, splitting tensile, and flexural strengths, static and dynamic moduli, and damping ratio of rubberized concrete through adopting three different prediction approaches with respect to the inputs of the model.
Findings
In general, the study's findings have shown that XGBoosting and FFBP models result in the best performances compared to other techniques.
Originality/value
Previous studies have focused on the compressive strength of rubberized concrete as the main parameter to be estimated and rarely went into other characteristics of the material. In this study, the capabilities of different machine learning algorithms in predicting the properties of rubberized concrete were investigated and compared. Additionally, most of the studies adopted the direct estimation approach in which the concrete constituent materials are used as inputs to the prediction model. In contrast, this study evaluates three different prediction approaches based on the input parameters used, referred to as direct, generalized, and nondestructive methods.
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Umut Uyar and Ibrahim Korkmaz Kahraman
This study aims to compare investors of major conventional currencies and Bitcoin (BTC) investors by using the value at risk (VaR) method common risk measure.
Abstract
Purpose
This study aims to compare investors of major conventional currencies and Bitcoin (BTC) investors by using the value at risk (VaR) method common risk measure.
Design/methodology/approach
The paper used a risk analysis named as VaR. The analysis has various computations that Historical Simulation and Monte Carlo Simulation methods were used for this paper.
Findings
Findings of the analysis are assessed in two different aspects of singular currency risk and portfolios built. First, BTC is found to be significantly risky with respect to the major currencies; and it is six times riskier than the singular most risky currency. Second, in terms of inclusion of BTC into a portfolio, which equally weights all currencies, it elevates overall portfolio risk by 98 per cent.
Practical implications
In spite of the remarkable risk level, it could be considered that investors are desirous of making an investment on BTC could mitigate their overall exposed risk relatively by building a portfolio.
Originality/value
The paper questions the risk level of Bitcoin, which is a digital currency. BTC, a matter of debate in the contemporary period, is seen as a digital currency free from control or supervision of a regulatory board. With the comparison of major currencies and BTC shows that how could be risky of a financial instrument without regulations. However, there is some advice for investors who would like to invest digital currencies despite the risk level in this study.
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Ceren Karaatmaca, Fahriye Altinay, Zehra Altinay, Gokmen Dagli and Umut Akcil
The aim of the study is to evaluate the perceptions of participants on the sensitivity training in conducting online context.
Abstract
Purpose
The aim of the study is to evaluate the perceptions of participants on the sensitivity training in conducting online context.
Design/methodology/approach
The researchers focus on the knowledge and attitudes of digital citizens as well as their perceptions on sensitivity training taking into consideration the technological aspects. In this qualitative approach, the available data were collected from 25 students from both graduate and undergraduate levels from different fields via an open-ended questionnaire in order to get their perceptions about creating a sensitivity training in the online context. In the questionnaire, metaphors were also used.
Findings
The themes derived from these metaphors and additional themes formed by narratives about technology and sensitivity equality feeding digital citizens allow ways to be examined and emphasize the importance of sensitivity training in technology and communication areas.
Research limitations/implications
Both direct and indirect thoughts of the participants are limitations of the study.
Practical implications
Preparing students adequately for sensitivity in the workplace is a constant teaching and learning challenges in higher education.
Social implications
This study focuses on universal values in a digital society in order to shed a light on sensitivity training in preventing conflicts in the global world.
Originality/value
The study focuses on the capacity of fostering digital citizens in e-society based on universal values and sensitivity training.